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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer (Data & ML) - **Company:** Unity Technologies - **Location:** Mountain View, CA, United States - **Salary:** $278,100.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Cloud Computing, Extract Transform Load (ETL), Data Systems, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Software Construction, Software Engineering, SQL Databases, Data Streaming, Data Processing, Real Time Systems, Apache Spark, Parallel Computation, Backend, Kubernetes, Low Latency, Apache Flink, Machine Learning Operations, Stream Processing, Data Pipelines - **Published:** July 2, 2026 - **Apply:** https://dejobs.org/x/x/F493B156A50345FBB3A3287F1803199C/job/ ## About the Role * Strong software engineering fundamentals with deep experience designing and operating large-scale distributed systems in production * Hands-on experience building production-grade ETL/ELT pipelines using Python, Java, SQL, or similar technologies * Experience with distributed processing frameworks such as Spark or Flink in both batch and streaming modes, including performance tuning and parallel computation * Understanding of how offline data systems integrate with online serving layers - feature stores, low-latency APIs, and real-time systems * Experience with cloud-native environments, containerized systems, Kubernetes, and workflow orchestration tools * Strong ownership mindset - focused on correctness, observability, and long-term maintainability * Experience with Go is a plus, particularly for collaboration on high-throughput feature serving services You might also have * Experience with ML infrastructure, feature stores, or model training pipelines * Background in ads, attribution, or monetization systems * Familiarity with experimentation and metrics infrastructure * Exposure to high-scale backend or platform engineering, This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English. ## Description This role goes beyond data processing. You'll own the full software lifecycle of pipeline systems - from architecture and implementation through to reliability, observability, and performance at scale - collaborating closely with ML, backend, and product teams to build durable, high-quality infrastructure that supports both offline training workflows and online feature serving. This role is ideal for someone who enjoys owning complex systems end-to-end, thinking deeply about correctness and scalability, and building software that other engineering teams depend on. What you'll be doing * What You'll Be Doing * Design, build, and operate scalable, production-grade data pipeline systems and curated feature datasets powering ads optimization and ML * Own end-to-end offline data flows from raw event ingestion to feature-ready datasets, with strong emphasis on correctness, reproducibility, and SLA compliance * Develop and maintain large-scale batch and streaming systems (Python / Java / SQL) with a strong focus on performance, cost-efficiency, and reliability * Build and contribute to our Feature Store platform, including integration with the high-throughput online serving layer (Go-based services) * Translate complex product and monetization logic into well-engineered, extensible systems serving analytics and machine learning use cases * Drive improvements in observability, testing frameworks, and quality standards across the platform * Lead architectural decisions and engineering best practices within the Feature Platform team ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [Best Countries for Software Engineers](https://www.wearedevelopers.com/magazine/267-best-countries-for-software-engineers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)